Enhancing FAIR compliance: A controlled vocabulary for mapping Social Sciences survey variables

Authors

DOI:

https://doi.org/10.29173/iq1118

Keywords:

Controlled vocabularies, longitudinal surveys, Knowledge graphs, Survey variables - Social Sciences

Abstract

The dynamic relationship among survey instruments and study entities like questionnaires, variables, questions, and response formats evolve in Social Sciences surveys. Researchers may need to modify variable attributes such as labels or names, question-wording, or response scales when reusing variables in survey design. Therefore, explaining these relations across different waves and studies is necessary to track how variables relate to each other. Although standards like Data Documentation Initiative – Lifecycle (DDI-LC) and DataCite model these relationships, these frameworks fall short of capturing the complexity of variable relationships. The DDI Alliance Controlled Vocabulary for Commonality Type employs codes—such as 'identical,' 'some,' and 'none'—to outline shifts in entities like variables; however, this approach is insufficient for disambiguating these relationships since they do not differentiate the variable attributes subject to change. We introduce the GESIS Controlled Vocabulary (CV) for Variables in Social Sciences Research Data to bridge this gap. This CV is designed to enhance semantic interoperability across various organizations and systems. Establishing explicit relationships facilitates harmonization across different study waves and enriches data reuse. This enhancement supports advanced search and browse functionalities. The CV, published via the CESSDA vocabulary manager, seeks to forge a semantically rich, interconnected knowledge graph specifically tailored for Social Science Research. This endeavour aligns with the FAIR data principles, aiming to foster a more integrated and accessible research landscape.

Author Biography

Claus-Peter Klas

Dr. Claus-Peter Klas, GESIS – Leibniz Institute for the Social Sciences, Team Leader "Data & Service Engineering" and Measure Lead in the NFDI consortium KonsortSWD in the department "Knowledge Technologies for the Social Sciences" . He received his PhD in computer science at the University of Duisburg-Essen and was a postdoctoral researcher in the Department of Multimedia and Internet Applications, Faculty of Mathematics and Computer Science, University of Hagen, Germany. His research focuses on information retrieval, interactive information retrieval, information systems, databases, digital libraries, preservation and grid and cloud architectures. He developed the software Daffodil founded on a nation research project and worked in national and European research projects such as The European Film Gateway, SHAMAN (Sustaining Heritage Access through Multivalent ArchiviNg) and Smart Vortex (Scalable Semantic Product Data Stream Management for Collaboration and Decision Making in Engineering).  He is currently responsible for several infrastructure projects within GESIS, such as da|ra, SowiDataNet or Missy, all concerned with providing information and data for social scientists. In addition, he leads the measure PID Services in the national research infrastructure project NFDI. In his team, they are developing an open source DDI suite to support getting DDI into operation.

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Published

2024-06-26

How to Cite

Saldanha Bach Estevao, J., & Klas, C.-P. (2024). Enhancing FAIR compliance: A controlled vocabulary for mapping Social Sciences survey variables. IASSIST Quarterly, 48(2). https://doi.org/10.29173/iq1118

Issue

Vol. 48 No. 2 (2024): IASSIST Quarterly

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Articles

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Copyright (c) 2024 Janete Saldanha Bach Estevao, Claus-Peter Klas

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